Perspectives on the Priorities for Bioinformatics Education in the 21 st Century

Transcription

1 Perspectives on the Priorities for Bioinformatics Education in the 21 st Century Oyekanmi Nash, PhD Associate Professor & Director Genetics, Genomics & Bioinformatics National Biotechnology Development Agency, NABDA/FMST Abuja. Nigeria Co-Author: Raphael D. Isokpehi, PhD Associate Professor (Microbiology & Bioinformatics) Bethune-Cookman University, Daytona Beach, Florida, United States Bioinformatics Curriculum Development Workshop University of Botswana, Gaborone, Botswana March, 2014

2 Outline 21st Century Biology Bioinformatics Definitions Scope of Bioinformatics Big Data Challenges in Biology Challenges in Data Science Addressing these challenges in Training Students to Master Bioinformatics Visual Analytics Conclusion Acknowledgements

3 NEW BIOLOGY IN THE 21 ST CENTURY What is the New Biology? SOURCE: Committee on a New Biology for the 21st Century.

4 Definitions Bioinformatics: Research, development, or application of. computational tools and approaches for expanding the use of biological, medical, or behavioral or health data including those to acquire, store, organize, archive, analyze, or visualize such data.

5 Focus of Bioinformatics Large Datasets Analyses in Bioinformatics predominantly focus on three types of large datasets available in molecular biology: macromolecular structures, genome sequences, and the results of functional genomics experiments (e.g. expression data). What is bioinformatics? A proposed definition and overview of the field.

6 Focus of Bioinformatics - Techniques Bioinformatics employs a wide range of computational techniques including sequence and structural alignment, database design and data mining, macromolecular geometry, phylogenetic tree construction, prediction of protein structure and function, gene finding, and expression data clustering. The emphasis is on approaches integrating a variety of computational methods and heterogeneous data sources. Finally, bioinformatics is a practical discipline. What is bioinformatics? A proposed definition and overview of the field.

7 BIOINFORMATICS RESEARCH CATEGORIES BROAD CATEGORIES OF BIOINFORMATICS RESEARCH AND DEVELOPMENT Genome Analysis Sequence Analysis Phylogenetics Structural Bioinformatics Gene Expression Genetic and Population Analysis Systems Biology Data and Text Mining Databases and Ontologies Bioimage Informatics

8 Making Discoveries from the Massive and Complex Genomics Datasets and Bioinformatics Results from H3Africa Projects The major bottleneck in genome sequencing is no longer data generation the computational challenges around data analysis, display and integration are now rate limiting. New approaches and methods are required to meet these challenges. National Human Genome Research Institute Strategic Plan: Charting a course for genomic medicine from base pairs to bedside

9 Examples of Projected Massive and Complex Datasets from H3Africa Projects (2013. Type 2 Diabetes Project 12,000 Cases and 12,000 Controls Sequencing of known T2DM regions Genome-wide genotyping arrays Whole exome/genome sequencing Body Composition Project African genome structure Phenotyping and sampling for Cohorts Genetic and environmental contribution to body composition (~12,000 individuals) These research investigations rely significantly on bioinformatics analysis and inferences from large and heterogeneous datasets obtained from populations inside and outside Africa.

10 Challenges in Data Science Source: National Consortium for Data Science, USA

11 VISUAL ANALYTICS ANALYTICAL REASONING VISUAL REPRESENTATION & INTERACTIONS DATA REPRESENTATIONS AND TRANSFORMATIONS PRODUCTION, PRESENTATION & DISSEMINATION

12 Ability to Use Tools for Making Sense of Data for Biology 90% Data Experts Statistics Bioinformatics Informatics Databases 10% Subject Matter Experts Genomics Proteomics Metabolomics Inability of Domain Experts to make sense of Massive data is a major challenge for advancing translational research

13 WHAT IS VISUAL ANALYTICS? Visual analytics is the representation and presentation of data that exploits our visual perception abilities in order to amplify cognition. - Andy Kirk, author of Data Visualization: a successful design process

14 WHAT IS VISUAL ANALYTICS? Multidisciplinary field defined as the science of analytical reasoning facilitated by interactive visual interfaces. An integrated approach combining fields such as visualization, human factors and data analysis which in turn integrates different methodologies as shown below:

15 Process of Visual Analytics Visual analytics is an iterative process that involves information gathering, data preprocessing, knowledge representation, interaction and decision making. The ultimate goal is to gain insight in the problem at hand which is described by vast amounts of scientific, forensic or business data from heterogeneous sources. To reach this goal, visual analytics combines the strengths of machines with those of humans. On the one hand, methods from knowledge discovery in databases (KDD), statistics and mathematics are the driving force on the automatic analysis side, while on the other hand human capabilities to perceive, relate and conclude turn visual analytics into a very promising field of research. Source: Keim et al, Visual Analytics: Scope and Challenges Visual Data Mining, LNCS 4404, pp , 2008

16 VISUAL INTERFACES

17 VISUAL ANALYTICS FOR MAKING SENSE OF BIG DATA Visualizations are absolutely critical to our ability to process complex data and to build better intuitions as to what is happening around us. Fox P and Hendler J. (2011) Changing the Equation on Scientific Data Visualization. Science 331: More Information at

18 MOTIVATION FOR VISUAL ANALYTICS IN BIOMEDICAL RESEARCH Availability in the public domain of datasets on human genomic variation that can be downloaded (as spreadsheet or text files) from web-based bioinformatics resources and supporting information of journal articles.

19 MOTIVATION FOR VISUAL ANALYTICS IN BIOMEDICAL RESEARCH "Future, rapid, and transdisciplinary research advances will depend on our ability to harness bioinformatics and the resulting data that come from computational biology. The challenge will be finding creative and more efficient ways to analyze, store, disseminate, and share data both new and from older studies widely and effectively. This will require transdisciplinary and other researchers to create standardized ontologies and nomenclatures, harmonize data systems, and increase access to shared databases that also provide innovative analytic tools." The Scientific Vision of the National Institute of Child Health and Human Development (NICHD) for the next 10 years includes a section on the Conduct of Science. NICHD Scientific Vision Next Decade.

20 CONCLUSIONS CURRICULUM FOR MASTER OF SCIENCE IN BIOINFORMATICS

21 H3ABioNet NABDA/FMST (Nigeria) Node Year 1 Highlights Education and Training 5 Training Workshops: Video Conferencing for Bioinformatics Research & Collaboration (Nov. 2012) Sequence Analysis and Bioinformatics Curriculum Development in Nigeria (July 2013) Visual Analytics for Human Variation Datasets (July 2013) Molecular Techniques (August 2013) Pre-Conference Workshop for Biotechnology Society of Nigeria (August 2013)

22 26 th Annual International Conference of Biotechnology Society of Nigeria (26-30 August 2013) Pre-Conference NABDA, Abuja, Nigeria NextGen Molecular Biotechnology Workshop National Biotechnology Development Agency Abuja, Nigeria; August 2013

23 H3ABioNet NABDA/FMST (Nigeria) Node Year 1 Highlights Outreach Established Nigerian Bioinformatics Research and Education Network

24 H3ABioNet NABDA/FMST (Nigeria) Node Year 1 Highlights Bioinformatics Services VISUAL DISCOVERY COMPARISON OF FUNCTIONS ENCODED IN LACTOBACILLUS REUTERI GENOMES Predicted Functions (Pfam) Urease Activity is unique to Lactobacillus reuteri , a rodent strain Filters for Interaction with Data

25 H3ABioNet NABDA/FMST (Nigeria) Node Year 1 Highlights Research Project (Probiotics Features) Protein secretion is important in biotechnological applications. Recombinant Proteins and Biopharmaceutical Proteins are of major importance in the biotechnology industry. A visual analytical integration of data sources of genes annotated for enzymes, transmembrane and signal peptide functions was designed. Additionally, the chromosomal alignment on the Integrated Microbial Genomes (IMG) system were determined for the genes of interest. The genome of Lactobacillus casei Lc-10 was the used for the research. Pipeline predicted gene cluster with gene for carboxypeptidases Carboxypeptidases are involved in the breakdown and reorganization of peptidoglycan Prediction: Biomolecular Network for Adapting to bile and acid stress by probiotic organisms. Chromosomal Alignment and Genomic Context ( and Biocyc.org) Oral Presentation by Atinuke Hassan at 26 th Annual Conference of the Biotechnology Society of

26 Master of Science in Bioinformatics 30 Credit-Hour Courses Open to students from Life Sciences and Medicine as well as Physical Sciences and Engineering Core Courses (18 Credit Hours): 1. Advances in Bioinformatics (3 Credits) 2. Computing and Informatics Foundations for Bioinformatics (3 Credits) 1. Computational Thinking, Visual Literacy, Human-Computer Interactions and Visual Analytics 3. Biological Databases and Bioinformatics Tools (3 Credits) 4. Research Methods in Bioinformatics (3 Credit) 5. Supervised Research (6 Credits) Priorities for 21 st Century Bioinformatics Need to Gain Deeper Understanding of Biological Systems

27 Master of Science in Bioinformatics Electives (12 Credit Hours) 4 courses related to project from 10 bioinformatics categories: Bioimage Informatics; Data and Text Mining; Databases and Ontologies; Gene Expression; Genetic and Population Analysis; Genome Analysis; Phylogenetics; Sequence Analysis; Structural Bioinformatics; Systems Biology

28 Acknowledgments H3Africa Bioinformatics Network (H3ABioNet) - - National Institutes of Health (U41HG006941) National Biotechnology Development Agency. NABDA/FMST, Abuja, Nigeria Visual Analytics in Biology Curriculum Network